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We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

Xuanwei City (formerly known as Xuanwei County) locates in the northeastern of Yunnan Province and is rich in coal, iron, copper and other mines, especially the smoky (bituminous) coal. Unfortunately, the lung cancer morbidity and mortality rates in this region are among China's highest, with a clear upward trend from the mid-1970s to mid-2000s. In 2004-2005, the crude death rate of lung cancer was 91.3 per 100,000 in the whole Xuanwei City, while that for Laibin Town in this city was 241.14 per 100,000. The epidemiologic distribution (clustering patterns by population, time, and space) of lung cancer in Xuanwei has some special features, e.g., high incidence in rural areas, high incidence in females, and an early age peak in lung cancer deaths. The main factor that associates with a high rate of lung cancer incidence was found to be indoor air pollution caused by the indoor burning of smoky coal. To a certain extent, genetic defects are also associated with the high incidence of lung cancer in Xuanwei. Taken together, lung cancer in this smoky coal combustion region is a unique model for environmental factor-related human cancer, and the current studies indicate that abandoning the use of smoky coal is the key to diminish lung cancer morbidity and mortality.

Promoting biodiesel industrialization is not only an important measure in addressing the energy crisis and global warming but is also a driver for industrial restructuring and rural development. To...

Developing a low-carbon economy is the only way for countries to achieve sustainable development. Carbon emission reduction policies and low-carbon technology (LCT) innovation play key roles in developing low-carbon economy. Under government reward and punishment regulations, based on the bilateral matching and evolutionary theories, this paper constructs an evolution model consisting of a manufacturer investing LCT and a supplier offering LCT to analyze multi-phase LCT investment strategies. Firstly, the profit optimization model of a green supply chain is constructed from the perspectives of centralized-matching (CM), decentralized-matching (DM), and mismatching (MM), and the spatial information internal evolution law of multi-phase LCT investment is described by the Markov chain. Then, a bilateral matching algorithm is proposed to solve the equilibrium solutions, and the evolution process of the three modes is analyzed by numerical simulation. Finally, based on the product green degree, we analyze the impact of subsidies and taxes on investment-production decisions. Analytical results show that the matching mechanism proposed in this paper can help supply chain firms to obtain stable matching and has a significant effect on the realization of "triple wins" of society, economy, and environment. The investment utility of CM is higher than that of DM and MM. Manufacturers are inclined to adopt LCT, and the investment level tends to be stable over time. Government reward and punishment regulations are helpful to motivate supply chain firms to invest in LCT, and the synergistic effect of subsidies and taxes is better than that of a single policy.

Abstract Since the adoption of the Kyoto protocol in 1997 and its entry into force in 2005, as well its aftermath such as the Doha amendment and Paris agreement, national policies have become more conscious of the usage of clean energy, mostly the different forms of renewable energy and nuclear energy. Ratifying countries and signatories had committed themselves to binding targets for the reduction of greenhouse emissions by 8% with respect to 1990 levels until 2012, also based on the particular contribution to global emissions from each country. This paper examines the integrational properties of clean energy consumption from eight emerging economies which are also high greenhouse gas emitters. The empirical results show that the clean energy consumption is stationarity for Brazil and Philippines by using a quantile unit root test without smooth breaks (Koenker and Xiao, 2004). However, after capturing the smooth breaks (Bahmani-Oskooee et al., 2018), we find the clean energy consumption of China, Pakistan and Thailand are stationary. The time-varying deterministic trend with smooth breaks is more fitted to the path of clean energy consumption in comparison to the deterministic trend without smooth breaks. The paper suggests economic insights useful for policy making.

A key factor in social development and sustainable urban expansion is the establishment of sustainable and affordable transport systems. This study aims to investigate the impact of transport infrastructure investment on environmental degradation and economic growth and to test the validity of the EKC hypothesis in China, India, Russia, and Japan over the period 1995-2020. The results show that GDP has a significant positive effect, and GDP2 and GDP3 have significant adverse effects on environmental degradation, respectively. These results confirm the validity of the inverted U-shaped EKC hypothesis in selected emerging Asian economies. Rail infrastructure investment has significant adverse effects, while road infrastructure investment and aviation infrastructure investment have significant positive effects on environmental degradation. Likewise, the impact of investment in transport infrastructure system (roads, rail, and aviation) on economic growth is positive and statistically significant. Country-level estimates confirm the validity of the inverted U-shaped EKC hypothesis in China, India, and Russia, while the N-shaped EKC is only valid in Japan. Investments in rail infrastructure based on modern rail systems that run on electricity are believed to be less polluting in the transport mix, help create sustainable and safe transport systems, and reduce emissions at the urban and intercity levels in emerging Asian countries. In addition, the growing impact of free trade on environmental pollution should be strengthened to harmonize the strict enforcement of environmental conditions dominated by trade agreements.

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress.

Abstract Although the “resource curse” hypothesis has been supported by many empirical studies focusing on the transnational and regional levels, there has always been a point of contention about the proper method of estimating and selecting natural resource indicators in literature. This paper proposes a mixed estimation method for panel data of 10 typical oil and gas resource-based cities in China from 1998 to 2015. The results show that resource industry agglomeration can mirror the distribution and dependence on the resource industry by location rather than by merely measuring the influence of the relative scale of resource extraction on economic growth. Using resource industry agglomeration as the main explanatory variable for regional economic growth verifies the resource curse hypothesis and shows the nonlinear characteristics of the negative correlation between resources and economic growth. Despite mostly similar indicator parameter estimates, marked differences exist in measured effects for material capital investments and technological innovation investments. The result of using resource industry agglomeration as the main explanatory variable is basically consistent with the economic theory and is more in line with observed reality than the alternative indicator. The research conclusions can provide evidence and data for index selection in the studies on the mediating effect of resource curse transmission and international comparison.

Abstract Global environmental change is driven by food production. Biogas from food waste is a better source of clean energy. Ghana’s energy strategy targets a 10% increase in renewable energy and modern biomass in the national electricity generation mix. Studies on the assessment of electricity generation potential and economic feasibility of biogas to electricity projects in Ghana’s major cities are scarcely available. This study assesses the electricity generation potential of biogas from food waste through anaerobic digestion technology. The municipal solid waste generation potential of Accra and Kumasi was estimated from 2020 to 2039. The potential theoretical methane yield from food waste was calculated using Buswell’s equation. The study analyzed anaerobic digestion projects’ economic feasibility using the total life cycle cost, net present value, investment payback period, levelized cost of energy, and internal rate of return methods. A sensitivity analysis based on two scenarios (optimistic and pessimistic) was performed to analyze the influence of changes in the composition of food waste, per capita waste generation rate, population growth rate, per capita GDP growth rate, discount rate, capacity factor, electricity generation efficiency, waste collection efficiency, and methane production potential on the economic feasibility of the projects. The main findings indicate that the amount of waste generation in Accra during the project life cycle is 899,000 t/y to 3,359,000 t/y, while that of Kumasi is 915,000 t/y to 3,159,000 t/y. The power generation potential of the project in Accra ranges from 80.43 to 300.49 GWh/y, and in Kumasi ranges from 60.63 to 209.31 GWh/y. Economically, the project is feasible in Accra and Kumasi. The net present value of the project in Accra and Kumasi is $217,800,000 and $156,100,000. The sensitivity analysis shows that the project is infeasible in all the cities with a discount rate exceeding 20%. When the discount rate exceeds 20%, the project becomes highly infeasible in Accra compared to Kumasi. This study will offer itself as scientific guidance for investment in biogas to electricity projects in Ghana’s cities.